Charlie Hart, a pharmacy informaticist at Mercy Health, a four-hospital health system in northern Illinois and southern Wisconsin, is advocating for a rethink of medical alerts. He envisions alerts that are so relevant they would no longer be ignored.

Hart advocates alerts at the most effective point in the workflow and for integrating information from the electronic health record, with a drug knowledge database. As he sees it, this makeover would reduce nuisance alerts. Instead, warnings would provide guidance to boost clinical care.

"The EHR contains a wealth of information about the patient," he said.

But the problem is that traditional medication alerts do not leverage most of this EHR information. Vendors can be slow to program new functionality, he said, because they have a 12-to-18-month release cycle and they need to support multiple drug database products.

In turn, this makes it hard for the EHR vendor to develop and support additional advanced medication alerts features that are not supported by all drug database vendors.

Hart suggested employing a consolidated clinical document architecture to combine the patient information from the EHR and the critical medication information from the drug vendor database vendor. Those steps would allow for the integration of patient-specific information into medication alert systems.

What information is often lacking for caretakers? Traditional medication alerts are triggered by the medication, Hart pointed out.

"Basic patient information like age, sex, comorbidities and key labs are not evaluated when deciding if a medication alert is applicable to the patient and should be displayed to the clinician," he explained.

So Hart champions more specific medical alerts.

Traditional drug-to-drug interactions evaluate drug pairs, and if two drugs are known to interact with a high enough severity, an interruptive alert will be displayed to the clinician, he said.

When assessing the drug-to-drug pair, key patient information is not evaluated, Hart added. However, by incorporating these additional patient-specific factors, the decision to display an interruptive alert to a clinician can be more precise and more specific to the patient.

Hart is scheduled to present at the HIMSS18 session, “Zeroing in on the patient to reduce alert fatigue,” at noon March 9 in the Venetian, Murano 3304.

A new survey out of Zebra Technologies found that an expected 97 percent of bedside nurses and 98 percent of physicians will use mobile devices in the hospital setting by 2022.

The Zebra study includes feedback from more than 1,500 nursing managers, IT decision makers and recently hospitalized patients in the United States, Brazil, China, Kuwait, Saudi Arabia, United Arab Emirates, Qatar and United Kingdom. All research was conducted in 2017.

Titled Future of Healthcare: 2022 Hospital Vision Study, it outlines the benefits of mobile technologies, as well as where the healthcare sector is headed as far as the topic is concerned. And according to the findings, the increasing adoption trend isn’t stopping anytime soon.

Better communication is also a benefit. Sixty-seven percent of nurse managers said improved staff collaboration comes with clinical mobility. Forty-two percent said such devices helped with point-of-care decision-making.

Additionally, 55 percent of hospitals said mobile technology helps reduce the cost of patient care, and 72 percent noted it improves the quality of patient care.

The survey narrowed in on patient opinions as well. The majority of patients expressed a general liking for clinicians using mobile devices in their care, with 77 saying they felt positive about it. Ninety-five percent are willing to share electronic health data from wearables with hospital clinicians. And 37 percent of patients said they brought health monitoring data to the hospital in preparation for a stay.

Looking ahead, respondents predict mobile technologies will become more integrated into the healthcare experience. By 2022, 92 percent of surveyed nurses anticipate being able to access medical and drug databases using a mobile device. By the same time period, 91 percent of nurses expect to access EHRs on mobile devices, and 88 percent anticipate accessing lab diagnostic results on devices.

And it’s not just nurses who will see an increase in mobile technology adoption. According to the survey, 96 percent of pharmacists will use mobile devices by 2022, compared to 42 percent in 2017. Ninety-six percent of lab technicians are expected to use the technology, versus 52 percent last year.

“[T]here is a higher demand for services and support that are not sustainable with existing resources and methods,” the study notes. “Hospitals are increasingly turning to technology and automation to reduce the strain on an already fragile system.”

Researchers studying CMS and AHA data published their findings in the American Journal of Managed Care. Specifically, Deyo et al. scrutinized information about patient mortality and readmission rates for heart failure and pneumonia in 2012 and 2013.

The AHA Annual Information Technology supplement gathered information from providers about their hospital’s health data sharing behaviors. Providers submitted responses about how frequently their hospital exchanged data between providers in their own health system, as well as with providers at outside health systems. AHA collected separate responses from providers about hospital sharing of radiology reports and lab results.

“Hospitals sharing diagnostic data through their EHRs with other hospitals and physicians within their system were associated with significant reductions in 30-day patient mortality scores,” stated researchers in the report.

Comparatively, sharing diagnostic EHR data with hospitals part of other health systems was associated with higher patient mortality scores – particularly for patients with heart failure.

Several factors may contribute to the correlation between EHR data sharing between health systems and higher patient mortality scores, researchers wrote.

“It is possible that hospitals within a system share EHR data more effectively due to team dynamics,” they suggested. “Further, as hospitals in different systems may have different EHR systems, there may be unique difficulties with sharing data across systems.”

Furthermore, the exchange of radiology reports may be limited by the fact that many patient health records do not contain radiology images.

“This may partially account for the differential between sharing with providers within and outside of systems because physicians within the system may be able to access the source images through other means when necessary,” wrote researchers. “Hospitals that solve the communication challenges associated with EHR data may be able to significantly reduce patient readmissions and mortality.”

Researchers also found communication between providers across EHR systems was generally lower than communication between providers using the same system. Seventy-two percent of hospitals shared radiology reports with hospitals within their system while only 36 percent shared radiology reports with hospitals outside their system.

Researchers observed a similar gap in the exchange of lab results within health systems as compared to between health systems.

Without significant improvements in EHR interoperability, the effectiveness of data sharing between hospitals will continue to lag behind data sharing within hospitals.

“If hospital sharing is limited by communication or compatibility among different EHR systems, the ability of EHRs to improve patient outcomes or access to care may be limited in the long run,” wrote researchers.

A lack of effective health data exchange between health systems may pose a significant threat to patient safety.

“Our study found some evidence that when hospitals do share EHR data with hospitals outside their system, patient mortality has the potential to increase,” researchers explained. “Therefore, although there may be benefits to sharing EHR data, it may be that hospitals are not yet able to effectively use EHR data from other hospitals as well as would be desired.”

“Thus, best approach for increasing patient outcomes through better provider communication of diagnostic information may not be simply expanding the degree of EHR data sharing among providers, but rather developing common standards when using different EHR systems to ensure that providers can share diagnostic information in ways that are easy for other providers to access and accurately interpret,” they concluded.

Organizations can use EHR timestamp data to improve clinical workflows by approximating the time it takes to complete common tasks. The data may be able to help providers with refining scheduling methods, analyzing EHR use, and quantifying how trainees interact with health IT systems, according to a study published in JAMIA.

In order to better understand how this dataset could help optimize interactions with the EHR, Researchers observed and collected workflow data from four ophthalmologists within Oregon Health and Science University’s (OHSU) Epic EHR system.

They compared the observations of workflows to timestamp data generated within the EHR, and found that EHR timestamps provided a reasonable approximation of workflow.

For three of the four physicians, the EHR timestamp measurements were within one minute of the observed reference exam times on average.

Additionally, 84.3 percent of the EHR calculated exam times were within three minutes of the observed times, indicating that this dataset could offer providers an accurate substitute for manual observation.

“There are many possible uses of this large set of timing data available from all EHRs,” the researchers wrote.

The team applied their findings to three different studies. The first used simulation models to test staff and exam room allocations and scheduling strategies that would prevent long wait times.

The models showed that adding staff and exam rooms didn’t reduce patient wait times, but scheduling patients who need more time toward the end of the day did help to control wait times throughout the day.

In addition to reducing patient satisfaction, long patient wait times can threaten healthcare revenue. This is especially true as the industry increasingly turns to value-based reimbursement models, in which clinicians are rewarded for providing timely access to quality care.

Researchers also applied their findings to a study on daily EHR use, and found that ophthalmologists use their EHR for an average of 3.7 hours per day. They also found that clinic volume and appointment complexity are two major factors that affect EHR use.

In general, researchers found that as patient volume increases, EHR use time decreases. However, they also found that when appointment complexity increases, so does EHR use time.

Since physicians with the highest clinic volume tend to see less complex patients, and vice versa, these findings suggest that patient volume is limited by the work required during exams. EHR use makes up a significant part of that work.

In fact, a 2017 study found that clinicians spend approximately 5.9 hours of an 11.4-hour workday on EHR documentation. This excessive amount of time spent on data entry has led to a spike in physician burnout, which negatively affects quality and cost of care.

Researchers also applied their findings to a third study that examined the impact of trainees on workflow. They found that trainees were associated with significantly longer appointment times for both fellows and residents.

While there are programs in medical schools that allow students to interact with EHR data before entering residency, the researchers write that these results show the effects trainees have on the “efficiency, productivity, and financial viability of academic medical centers.”

The application of EHR timestamp data to studies like this can lead to better planning and reimbursement models for clinics’ training activities, the researchers state.

Using this type of metadata can help justify EHR improvements. EHR optimization requires technology experts to assess the current system in place, and to examine how users interact with the EHR.

Knowing the factors that significantly impact EHR use can help experts decide where to make improvements, and ultimately increase EHR efficiency.

Studying clinical workflow is a key way to gain insight for improving physician productivity. Providers are currently under pressure to see more patients in less time, and many believe that EHRs have only added to time pressure.

However, as the researchers indicate, workflow studies often require observational data that is too resource-intensive. The results of this study show that existing EHR timestamp data can help organizations boost physician productivity and increase patient satisfaction.

“These applications show the power of using existing EHR timing data for clinical workflow studies that would not have been possible otherwise and the possibilities for applying these methods to studies in other clinical settings,” the researchers concluded.

The Centers for Disease Control and Prevention (CDC) has formed a new initiative focused on leveraging technology to get clinical guidelines in front of healthcare providers.

Through the initiative known as “Adapting Clinical Guidelines for the Digital Age,” CDC officials are looking for feedback from clinicians, EHR and third-party app developers and public health agencies about the best ways to disseminate clinical guidelines. The agency plans to hold a public meeting with stakeholders the week of February 5, according to a notice (PDF) posted this week to the Federal Register.

The CDC plans to use information from that meeting to pilot test new processes for guideline development and implementation.

“Because there are multiple roles in developing and disseminating clinical guidelines, it is important to get a comprehensive understanding of the current challenges in translating guidelines in order to develop a standardized process for the future,” the notice stated.

CDC spokesperson Melissa Brower told FierceHealthcare the initiative is "a natural extension" of an agencywide working group formed in 2016 looking at ways to ensure CDC guidance is used in practice.

Using technology to quickly get information to clinicians, particularly during public health emergencies, is an issue the CDC has highlighted as an ongoing challenge. At a December meeting hosted by the Office of the National Coordinator for Health IT, the CDC’s Chesley Richards, M.D., who directs the Office of Public Health Scientific Service, said the Ebola outbreak led to “some soul-searching” about how the agency can improve clinical decision support.

Richards added that the CDC is especially interested in extracting data from EHRs to quickly identify outbreaks, while also limiting the reporting burden for physicians.

Harvard Pilgrim Health Care is financing expansion of the eConsult telemedicine platform to two new Connecticut health systems, improving access to specialist services for patients and their doctors.

One of New England’s largest health plans is investing in a telemedicine platform that enables patients and their primary care providers to access specialty consults.

Harvard Pilgrim Health Care has awarded $32,000 in grants to two Connecticut health systems to expand the eConsult program, an innovative telemedicine program launched in 2015 by Middletown, Conn.-based Community Health Center (CHC) and now being used in about a dozen states across the country, including New York, Delaware and California.

Harvard Pilgrim has awarded $20,000 to Community eConsult Network to launch a year-long pilot through the Value Care Alliance (VCA). The pilot began last month at Middlesex Hospital Primary Care in Middletown nad is expected to expand soon to other VCA member organizations.

“The goal of this pilot program is to make it easier for patients to get the care they need by helping their primary care physicians obtain timely specialty consultations,” Russell Munson, MD, Harvard Pilgrim’s Connecticut Medical Director, said in a press release issued last November, when the grant was made. “In many cases, it will eliminate the need for additional appointments as well as time and travel by using technology to access prompt, high quality specialty care for patients. eConsults will help with access to specialist medical opinions, prescribing, ordering tests and the maintenance of patient medical records, bringing ease and efficiency to patients.”

In addition, the health plan has issued a $12,000 grant to help CeCN launch the telemedicine platform for the new Haven-based Community Medical Group. CMG’s Independent Practice Association serves New Haven, Shoreline and Fairfield counties with a network of some 900 primary care practitioners.

Working with the Weitzman Institute – CHC’s research and innovation arm - and Safety Net Connect, a California-based developer of online care coordination services, CHC launched its eConnect pilot in 2015. Working at first with cardiac care patients, the program routed all specialist referrals from CHC providers through an online system that allows the specialist to review the case online. This includes access to the patient’s medical record and any questions the primary care doctor may have about his/her diagnosis and treatment so far.

The model was originally developed to help federally-qualified health centers coordinate and improve care for the hard-to-reach Medicaid population.

CeCN officials say between 60 percent and 90 percent of the specialty consults have been resolved by the eConsult service since its launch, eliminating costly and unnecessary specialist appointments. More than 14 specialties are now available through the telemedicine platform, including cardiology, dermatology, gastroenterology, pediatric cardiology, orthopedics and pain management.

“Our work has clearly shown what a significant difference eConsults can make for primary care providers and their patients,” says Daren Anderson, MD, CHC’s vice president and chief quality officer and director of the Weitzman Institute. “They help to ensure that patients get access to the best care quickly and efficiently. Harvard Pilgrim is helping us to spread this work across Connecticut, helping build a stronger and more effective primary care system.”

Based on the 2015 pilot’s success, CHC and the Weitzman Institute created CeCN, a non-profit to manage and run the program. Shortly thereafter, the Centers for Medicare & Medicaid Services approved the program for Medicaid reimbursement.

“With limited specialty providers available to treat Medicaid patients, appointment wait times can be as long as a year, leading to healthcare disparities, higher rates of disability and complications in chronic diseases,” CMS officials said in a 2016 press release. “SNC’s eConsult system has been proven to increase access to timely, cost-effective specialty services for underinsured and underserved patients, many of whom live in rural areas with limited access to specialty care.”

Associate Vice President John Donohue divulges the system’s approach to telemedicine and videoconferencing, including the tech and governance components hospitals need to succeed.

While there is nothing really new about video-based collaboration — or even telemedicine for that matter — a technology ecosystem is emerging to make next-generation medical visits and business interactions mainstream. That means it should be a core component of hospital’s IT planning process.

Video technology and clinical integration capabilities have reached a maturity level that makes enhanced collaboration a reality, and potentially a competitive differentiator.

Recently, we developed a three-tier video strategy for collaboration and telemedicine. Our strategy addresses a wide range of clinical visit types and business scenarios. Yet it is dynamic and agile enough to scale and handle future state requirements. For example, our new patient bed tower will be opening in 2021 and we are preparing to include types of video technologies that might be built in to the core requirements of this acute care facility.

Additionally, our strategy addresses the legacy video technologies already in place across the enterprise with a transformation plan. Lastly, this scheme fits into our planning tenant of common systems, centrally managed and collaboratively implemented.

The first component of our plan addresses clinical grade video technology. This offering is designed for more clinically oriented requirements. Examples of this type include video technology within our OR suites for grand rounds and physician education. Additionally, this is the platform used for connected health (such as remote patient monitoring) and telemedicine solutions that touch patient care. This platform is designed with high resilience for maximum availability and has been integrated with our EHR for billing purposes. The collaboration required to design and build an integrated EHR/telemedicine capability is significant — but it paves the way for some game changing telemedicine offerings to your patient community.

Room-based video conferencing is another offering designed as a standards based collaboration technology to use throughout our health system which has grown exponentially in size and geographical footprint. Picking the right technology partner and a solution that is both easy to use and scales appropriately is instrumental in our success. We are also able to collaborate more easily outside the organization communicating with U.S. and even overseas business relationships. Interoperability is the name of the game when it comes to bridging outside your organization. This interoperability should include other industry leading room service providers and cloud service providers. For our room based video conferencing, we have templates that help guide new implementations and budget estimates for upcoming construction projects. These include one for senior executive/trustee level rooms, one with a higher level of technology for specific requirements and one for basic audio/visual needs. All of our rooms are tied back to a central control center for monitoring, support and troubleshooting.

Lastly, the mobile and desktop video conferencing is the most flexible of our tiers and is used for collaboration among staff level folks across the organization. Here we leverage our network infrastructure across to deliver unified communications capabilities. Cost is low and it’s easy to implement. The technology is already paying dividends for collaboration.

Most recently, we are piloting a concept called “VC in a Box”. This concept includes the capability to have a mobile video conferencing configuration that can be moved around the organization for special events that don’t occur in a previously designed video conferencing room. The early success in this pilot leads me to believe that we may wind up with several of these setups as a new offering.

When rolling out video technology like this across a broad, diverse and complex organization, communication becomes paramount. How you explain these offerings (via a service catalog) and make it easy for the user community to select the right technology at the right time is key to acceptance and driving the benefits of its use. We created a video technology governance committee that steers the direction and becomes a set of champions. This group ultimately helps us with communications and the development of an effective portal for how to engage the services and maybe most importantly how to get a session scheduled and get the support that is needed.

Our portal offers white glove support and even addresses things like re-arranging the room for an event and having food and beverages delivered. Lastly, the portal allows for calendar synchronization so that it is tightly integrated with the scheduling of the room itself.

Ultimately, having an effective and easy to use video technology ecosystem can allow a growing organization to drive down travel costs, increase collaboration and ultimately provide better patient care to drive enhanced outcomes.

Genomic-informed therapy recommendations are becoming available for clinical decision support at the point of care.

Progress in genomic sequencing has led to some exciting breakthroughs in clinical therapies. And now, information about those therapies is becoming available for use within the EHR.

Marc S. Williams, director of the Genomic Medicine Institute at Geisinger, reported in a HIMSS Learning Center webinar today that integration between databases of genomic findings and most EHRs is now possible due to work based on funding by the National Human Genome Research Institute.

“Context-sensitive links embedded in EHR systems,” Williams said, “can be used to provide links to online clinical resources to help anticipate clinicians' information needs.” He said the capability is available for addition to any Meaningful Use compliant system.

The work is a collaboration between two NHGRI projects, the eMERGE network and ClinGen. eMERGE is a national network which studies and pilots genomic medicine translation through discovery, implementation, tools, and policy; it is working on EHR integration. ClinGen is building an authoritative central resource that defines the clinical relevance of genes and variants for use in precision medicine and research.

Williams said these EHR integrations have enabled pharmacogenomic information to be made clickable, allowing clinicians to navigate directly to a view of guidelines on recommended therapies.

“We have res-useable reliable algorithms that can be used across almost any EHR,” he said. “It also provides links to guidelines on CLIA certified genetic testing, which is helpful to clinicians who may struggle with where to send out for genetic tests.”

NHGRI was established in 1989 to carry out the role of the National Institutes of Health (NIH) in the International Human Genome Project. The eMERGE Network is comprised of 13 sites, including 2 central sequencing and genomic centers (CSG) and one coordinating center. Each site maintains its own biorepository where DNA specimens are linked to phenotypic data contained within EMRs.

It has a goal to identify 25,000 participates with 100 clinically relevant genes.

The member organizations are Children’s Hospital of Pennsylvania, Cincinnati Children’s Medical Center, Columbia University, Geisinger, Kaiser Permanente Washington with University of Washington and the Fred Hutchison Cancer Research Center, Harvard University, Mayo Clinic, Meharry Medical College, Northwestern University, Vanderbilt University, University of Washington, Baylor College of Medicine, and Partners/Broad.

A report demonstrates six ways public health agencies can use EHR data to improve community health.

EHR data could allow for dramatic improvements in addressing community health challenges, according to a recent report released by the de Beaumont Foundation and Johns Hopkins Bloomberg School of Public Health.

Researchers presented six use cases to illustrate how EHR data could help public health agencies make progress on childhood asthma – a common and preventable chronic illness.

“Asthma is a disease of individuals, many of whom require daily medication to prevent serious exacerbations,” wrote authors in the report. “At the same time, asthma is a disease of the community, with poor housing conditions and air pollution leading to significant clusters of illness.”

Utilizing EHR data can improve surveillance, geographic analysis, identification of high risk patients, clinician engagement, and evaluation of interventions for individuals with childhood asthma. Furthermore, researchers suggested these uses for EHR data could also be applied to other, more pressing public health challenges such as the opioid epidemic.

In addition to each use case, researchers also employed standard legal research methods and consulted secondary sources and practice materials to analyze how HIPAA recognizes the need for public health agencies to access protected health information (PHI).

“To do so responsibly and successfully under the law, public health agencies must be clear about their goals, specific in their requests, and take steps to assure the confidentiality of key data,” wrote researchers.

As part of the first use case, researchers demonstrate how EHR data can be used to determine whether rates of childhood asthma are rising or falling.

“Data reflecting time trends of asthma morbidity might allow the health department to strategically time the implementation of interventions to maximize impact,” suggested researchers. “Time series data pertaining to asthmatic episodes might also be used to inform health messages to the public about environmental conditions that are likely to trigger asthma attacks.”

The health department could request a weekly data file from each area hospital to obtain information about residents under the age of 21 that were diagnosed with asthma during an emergency department visit or hospital admission.

“The health department will combine and analyze the hospital data on a weekly basis for internal use,” wrote researchers. “These reports will inform program development and facilitate monitoring of the burden of disease.”

To determine the location of housing conditions that may trigger childhood asthma, researchers explained that public health officials could request a regular data file from area hospitals and identify specific geographic areas of the highest risk.

“Once identified, the health department will assess the external air quality in the vicinity and offer the services of environmental inspectors to assess home hazards to all in the area,” stated researchers.

The third example researchers illustrate to show the potential uses for EHR data involves identifying children with severe asthma that could benefit from evidence-based, at-home services. Again, the health department could request a regular data file from area hospitals at least weekly.

“The health department will combine these data to develop a registry of children admitted to the hospital for asthma,” researchers stated. “Those most frequently admitted will be contacted by the health department and offered home visits and care coordination.”

The fourth use case demonstrates how EHR data could be useful in allowing health departments to develop a tool to flag patients with severe asthma and alert clinicians about the existence of care plans.

“The health department is interested in alerting emergency departments when children with severe asthma are present, so that clinicians can check the asthma care plan and understand specific patient needs,” wrote researchers.

In this instance, the health department can maintain a registry of children with severe asthma and link the registry to an app containing a care management plan for each child.

The fifth use case addresses how health departments can use EHR data to assist with medication adherence.

“For identified children who are not receiving a regular prescription for a controller medication, the health department will provide outreach to the families of patients and their primary care doctors to support improved access to therapy,” they wrote.

Finally, public health officials can use EHR data to determine the impact of specific interventions on reducing or improving cases of asthma.

The health department can combine data files from hospitals to assess health trends for different groups of patients including the following:

Those that live in geographic areas that received specialized interventions compared to those that did not

Those that were offered case management services compared to those that were not

Those who have an updated asthma care plan compared to those that did not

The health department can use this information to decide whether to continue with specific intervention efforts or change them.

In addition to these six use cases, researchers also provided information about HIPAA, how to legally share and use health data with public health agencies, and other areas pertaining to data exchange for public health services. Researchers also offered recommendations to public health agencies interested in utilizing EHR data to improve community care.

Here are some of the ways in which each of these technologies is already making waves in the medical industry.

Artificial Intelligence

Analysis from the consulting giant Accenture predicts that, "key clinical health AI applications can potentially create $150 billion in annual savings for the US healthcare economy by 2026." One of the major cost-saving opportunities for AI lies in preventing health insurance fraud, which costs Americans as much as $230 billion dollars annually. That's a full ten percent of all national healthcare spending. Fraud detection programs powered by artificial intelligence could drastically reduce this burden.

AI also has the potential to elevate medical research by identifying relevant data and information that lies out of reach for traditional search engines and databases. Gunjan Bhardwaj, CEO and Founder of Innoplexus, said, "There is a wealth of medical, research, and patient data that is often unreachable for researchers, or it's spread across hundreds of sources." AI and machine learning technologies can democratize the field by reducing the time, effort, and cost of medical research.

Blockchain

A recent analysis by Deloitte concluded that "blockchain technology has the potential to transform health care, placing the patient at the center of the health care ecosystem and increasing the security, privacy, and interoperability of health data." In particular, blockchain technology may be the key to super-charging one of the most important medical trends of the last decade: medical record sharing.

Systems that allow the sharing of digital medical records between various providers have dramatically improved the continuity, efficiency, and outcomes of patient care. However, given the personal nature of medical records, security is always a concern. Blockchain technology promises to offer both the security necessary to ease privacy concerns and the efficiency necessary to improve patient care. As a recent post on IBM's blockchain blog put it, "better data sharing between healthcare providers means a higher probability of accurate diagnoses, more effective treatments, and the overall increased ability of healthcare organizations to deliver cost-effective care."

The security offered by blockchain technology may also benefit drug research, as people may be more willing to participate in clinical trials if they are confident that their private information will remain secure.

By reducing the cost and improving the efficacy of medical research and care, these technologies will democratize access to high-quality medical treatment. They will also lower the barriers to entry for new companies hungry to bring innovative solutions to the medical field. Entrepreneurs, physicians, and patients alike will enjoy the benefits.

Big Data Analytics

Big Data has already taken other sectors to new heights of innovation and productivity. Business, finance, and even politics have been transformed by the seemingly endless analytical insights offered by big data. There are good reasons that healthcare should be next.

Drug development is one area in which data analytics can make a big difference. The democratization of medical data opens the doors for start-up pharmaceutical and research labs to disrupt the drug development industry. Bhardwaj explained, "Our goal is to democratize that data, by leveraging the latest in A.I. and machine learning technologies to give professionals across the life sciences access to information that will help them achieve their goals faster and at a lower cost." Data is a valuable resource that has the potential to drive innovation in this important field.

Big data can also enable healthcare providers to predict patient needs more accurately and efficiently. Data and analytical tools allow physicians to identify risk factors and to approach patient care from a predictive perspective rather than a reactive one. Doctors can more effectively diagnose conditions, prioritize care and resources, and improve patient outcomes.

To support integrated care teams, organizations need to look at where there are gaps appropriate for technology to fill

As health care organizations seek to deliver the highest quality of care to their communities while containing health care costs in the process, coordinating patient care effectively across the continuum is more crucial than ever. The mix of providers involved in a given patient’s care has grown as medicine has become increasingly specialized. As providers, we have an obligation to understand what each episode of care offers the patient and to ensure those episodes are not viewed in isolation, but rather as part of an arcing narrative with the patient at its center.

And yet, given the overwhelming demands on our time, how can we as providers gain a true sense of the other potential contributors to our patients’ care? And how can we begin to collaborate around that care when we don’t always know or have an effective means of communicating with the other providers on a given care team? When deployed correctly, these are two areas in which technology can be an ally to both health care organizations and providers while also supporting better outcomes for patients. Of course, the care continuum for a given patient frequently encompasses a wider network of caregivers, such as social workers, physical therapists and home health aides, that technology can also help integrate, but this piece focuses on the initial core of providers partnering around patient care.

Constructing optimal care teams

When it comes to referrals, the prevailing strategy for clinicians is to to build a personal network of a few trusted providers with whom they have worked reliably over time. While this model fosters trusting relationships among providers, especially if they interact on a regular basis, it may not always be in the best interests of their patients. There are certainly benefits to providers being familiar with each other, but a clinician’s go-to provider for a given specialty may not be the best option for every patient. For example, the gastroenterologist one happens to know who performs colonoscopies exceptionally well may not be best suited to treating a patient with hepatic steatosis.

Providing the best care requires creating teams with provider expertise tailored to each individual’s clinical needs. Therefore, health care organizations maintain “rosters” of providers with different areas of expertise. These tools, also called provider directories, give organizations visibility into their provider networks and the skill sets of the providers therein.

A provider directory is a key part of the foundation for effective care coordination. When evaluating an organization’s directory, leaders should consider the following questions:

Is there one central directory for the organization or are there multiple directories?

What level of detail does it contain about providers, clinical and otherwise? Does it give referring providers the information they need, including the depth and breadth of other providers’ clinical expertise, to make appropriate care decisions?

What are the sources of information for the directory? When there are discrepancies, what’s the process for reconciling them?

Are providers involved in contributing to or verifying their information?

What are the organization’s processes for determining which providers should have which clinical areas of expertise listed? Who has ultimate accountability for the accuracy of the information?

Are there vetting processes in place to validate that a given provider should (or shouldn’t) have a particular area of expertise listed?

Do providers and others have a clear understanding of how to submit profile updates?

A provider directory has an essential role to play in enabling providers to look beyond their personal network for referrals. Thus, when looking to drive behavior changes and facilitate collaboration around patient care, organizations must take a close look at what information they make available to their providers.

Enabling communication within care teams

Ensuring that providers can build and understand their care teams is the first key step in facilitating integrated care teams and an area where technology can be a powerful enabler. After that, it’s equally important to enable providers to communicate with each other, stay informed about their patient’s care activity and close the loop on care events.

To maximize the effectiveness of integrated care teams, once clinicians have selected a provider they must be able to send referrals using a modern process. However, provider networks are continuously evolving; widespread variation in their infrastructure curtails the potential for electronic health records to enable this communication. Providers can sometimes find it a challenge to communicate efficiently, close the loop or understand what’s happening next for the patient. Did the patient show up? What did the provider determine? What’s the patient doing next? The inability to answer such questions easily is not only frustrating for providers but also hinders intervention by referring providers when necessary (e.g., if a patient doesn’t show up to an appointment). Similarly, it prevents the receiving providers from being able to ask questions or request more information without calling.

To be sure, there is still a place for phone-based communication among providers. In some instances, this is actually the best option, and technology shouldn’t aspire to replace it. Rather, technology should supplement these interactions when there is both an actual need and tangible benefit to deviating from traditional communication methods. To support integrated care teams, organizations need to look at where there are gaps appropriate for technology to fill, such as secure text messaging, e-consult solutions and referral mechanisms.

Making technology work for care teams

Building a truly coordinated and continuum-focused approach to patient care requires a fundamental shift in both how health care organizations think about constructing care teams and how they facilitate care coordination within them. Technology has a powerful role to play here, first by enabling organizations to enhance their provider directories and second by facilitating communication between often geographically dispersed providers. Both areas are critical; without the first, providers are limited in their ability to identify the right providers for each patient’s specific needs, and without the second they are limited in their ability to communicate effectively with the other providers involved in a patient’s care.

While both of these technology initiatives start at the organizational level, a proactive effort to include providers in their planning and implementation is essential for achieving the desired impact on care delivery. Technology can serve as a powerful enabler, but any effort to enhance how integrated teams form, collaborate and deliver care must involve the humans who will ultimately deliver that care. With appropriate technology, and the support of those who will use it, health care organizations can overcome key barriers to care coordination and help teams achieve better outcomes for their patients.

Health care providers are getting into the artificial intelligence game, and the technology is being used in myriad ways.

Just six months after El Camino Hospital in Silicon Valley implemented artificial intelligence technology, the rate at which patients suffered dangerous falls dropped 39 percent. The key, alongside additional fall prevention strategies, was a software program that predicts which individuals are most likely to fall by combing over electronic health records for risk factors and merging the data discovered there with real-time tracking of patients.

"Every time a patient pushes a call light or hits a bathroom or bed alarm, it's recorded," says Cheryl Reinking, chief nursing officer at El Camino. The software takes that information and compares the rate at which a patient is requesting assistance to data such as what surgeries he's had or which medications have been prescribed.

These data are all processed through "machine learning" – a form of artificial intelligence whereby computers take in new information and perform tasks based on it without being reprogrammed to do so. In this case, the program "learns" if a person may be more likely to fall based on his behavior and treatments. "Then it pushes an alert to the nurse saying 'your patient in room 2308 is at risk right now for falling,'" Reinking says, after which that individual might be moved closer to the nursing station or monitored via video.

The ability of computer systems to assume tasks for humans has improved efficiency in virtually every industry, from manufacturing to transportation. Now hospitals are getting into the game, deploying AI to take on challenges from diagnosing patients more quickly in the emergency room and streamlining communication between doctors to lessening the risk of complications so patients can go home sooner – and avoid being readmitted.

One big way in which patients will benefit directly is in AI's ability to help clinicians make diagnoses. IBM brought AI into the mainstream of medical care a few years back, when it offered its "Jeopardy!"-winning system Watson to cancer centers to help oncologists determine the best treatments for patients. Physicians can now plug patient diagnoses into IBM's Watson for Oncology and instantly receive treatment recommendations based on patient data and information pulled from reams of medical journal articles.

Since Watson's initial baby steps, AI has quickly demonstrated its potential to be a game-changer in many areas of health care. Other technology developers, for example, are focusing on software that can read CT scans and other medical images and then suggest the most likely diagnosis by reviewing similar images stored in patient databases. And these programs can accurately process these tasks far faster than human technicians. AI's potential is so promising that some experts predict it will eventually be every doctor's and nurse's go-to assistant.

James Shoemaker, a physician with Elkhart Emergency Physicians in Elkhart, Indiana, can attest to its value. Shoemaker uses a program called VisualDx, which allows him to input medical images along with patient symptoms and immediately pull up a list of possible diagnoses. One parent brought in a child with a bad rash that turned out to be a rare disorder called Stevens-Johnson syndrome, he recalls. "I had an idea it could be that," Shoemaker says. The program "reinforced my diagnosis and helped me figure out the next step."

New York University's Langone Medical Center is developing one AI system to predict which patients are likely to develop the dangerous condition sepsis and another that alerts doctors to cases of heart trouble. "If you're admitted to the ER for pneumonia, the people who are treating you may not think about the fact that you also have congestive heart failure," says Michael Cantor, an internist and associate professor in the hospital's departments of population health and medicine. The system will go through each patient's record when they're admitted and automatically alert cardiologists to anyone who has heart failure, so they can advise on how to avoid treatments that might exacerbate that condition.

Artificial intelligence is also being employed to improve efficiencies. Several hospitals are experimenting with technology to optimize schedules for surgeries and imaging tests by predicting how long each procedure that's scheduled in a particular day will take. Partners HealthCare, which includes Brigham and Women's and Massachusetts General hospitals in Boston, announced in May that it will work with General Electric over the next 10 years to incorporate AI into virtually every area of patient care, including developing applications to cut down on unnecessary biopsies and streamline administrative tasks for doctors.

These are all tasks that people traditionally do, but sometimes machines do them better, says Michael Williams, president of the University of North Texas Health Science Center. "Reducing ER wait times, improving surgical workflows – those are key to improving the patient experience, and AI has a real role to play."

If there's anything that's holding back the widespread adoption of AI in hospitals, it's nagging doubts that the technology will produce a good return on investment. A 2017 survey by HIMSS Analytics and Healthcare IT News found that 35 percent of health care organizations plan to adopt AI within two years, but 15 percent of respondents said they couldn't make a business case for doing so. And more than 20 percent said they thought the technology was still underdeveloped.

The field of AI in health care suffered a setback in February, when the University of Texas MD Anderson Cancer Center put its partnership with IBM on hold after an internal audit reported that the institution's effort to incorporate Watson into patient care ultimately failed to meet its goal. In an email, a spokeswoman for MD Anderson said the organization is constantly reviewing technologies that promise to improve cancer prevention and patient care, and that "while a variety of approaches have been examined, a final approach using this technology to benefit patients has not been determined at this time."

Rob Merkel, general manager of oncology and genomics for Watson Health, says the company is making headway in the market with Watson for Oncology, which IBM developed with Memorial Sloan Kettering Cancer Center in New York. And he cites research the firm did with MD Anderson that he believes shows Watson's potential. "We demonstrated 95 percent concordance with what Watson would recommend as a treatment option versus what an MD Anderson physician would recommend," he says.

Meanwhile, the University of Pittsburgh Medical Center is funding a project aimed at using AI to get treatment ideas for individual cancer patients by comparing genomic information from their tumors to molecular data housed in the Cancer Genome Atlas – an interactive database maintained by the National Institutes of Health containing data on 10,000 tumor samples of 33 cancer types.

So could AI someday even substitute for doctors? Peter Slavin, president of Mass General, believes people will always be essential to delivering high-quality care – but that machines will become increasingly vital to making that care better. Improvements in computing power and the ability of computer programs to emulate neural networks in the brain unlock enormous possibilities for the use of AI in medicine, Slavin says. "We haven't really even begun to see its impact."

With opioid addiction officially a public health emergency in the United States, it’s more important than ever that physicians and other clinicians carefully document a patient’s opioid use in the electronic health record.

To help providers better document the use and abuse of opioids, the American Health Information Management Association (AHIMA) has created an opioid addiction documentation tip sheet that gives examples of proper documentation that complies with the seven characteristics of high-quality clinical documentation. Those factors include providing clear, precise, complete information.

AHIMA spokesperson Mary Jo Contino said proper documentation and EHR interoperability is often overlooked as a tactic to help reverse the country’s opioid epidemic. Fewer than 30% of health system EHRs are fully interoperable, and less than 20% actually use data transferred from another provider, according to a new study.

It’s important that physicians and other healthcare providers accurately record information in the EHR when an individual using or abusing opioids visits their office. Without national communication standards for health information exchange, that documentation is often not shared among healthcare system facilities or across state lines, allowing people with addictions to seek opioids from multiple physicians.

Meanwhile, Prescription Drug Monitoring Programs (PDMPs) are gaining traction as opioid overdose deaths have skyrocketed. Last month, the President's Commission on Combating Drug Addiction and the Opioid Crisis recommended state and federal PDMPs be interoperable within 12 months.

The tip sheet lists the seven characteristics of quality documentation, provides scenarios of how to meet the criteria and provides an example of poor documentation frequently seen when treating patients with opioid prescriptions. The tip sheet also has examples of a proper documentation statement.

Last month, President Donald Trump declared the opioid epidemic a national public health emergency. AHIMA says high-quality clinical documentation will guarantee that the data which drives research and education about opioid addiction is based on correct information.

The world of healthcare and health information management (HIM) is quickly moving to meet the demand of analyzing and making sense of all the data that is collected—and, ultimately, turning it into useful information.

Data is defined as “facts and statistics collected together for reference or analysis.” Information is “facts provided or learned about something or someone, ‘a vital piece of information.’” The question of how information governance and data governance differ from each other is addressed in the Information Governance FAQs on AHIMA’s website:

Data governance “is primarily concerned with policies and strategies that address the creation and use of granular data as inputs into a system,” i.e., master data management, metadata management, data models and architecture.

Information Governance is concerned with “lifecycle management of this data and information, including its use, protection, and preservation,” i.e. health information exchange, compliance audits, e-discovery and retention of records.

So the two are related and data governance is actually a domain within Information Governance.

HIM professionals are tasked with improving the consistency, reliability, and usability of data assets while optimizing electronic health record (EHR) interfaces. This is necessary to eliminate duplicate records, to address problematic workarounds, and to maintain patient safety. If the data is incorrect (or missing completely) in the case of allergies, current medications, past procedures, and health conditions of a patient, it can be detrimental to the course of treatment and care of the patient.

Additionally, providers are now trying to pull useful information out of the data in their EHRs to support the goals of healthier patients, lower costs, improved performance, and increased staff and patient satisfaction rates.

Merida Johns defines Big Data as “the concept of large volumes of complex and diverse data.” We must utilize our Big Data assets and extract business and clinical value from them. Strong information governance and data governance practices will allow healthcare organizations to maximize the value of their data and information to use in order to meet strategic goals and other requirements. Some of the top challenges facing organizations—and thus opportunities for HIM professionals to step up and demonstrate their value to the organizations—who wish to begin Big Data analytics, according to an article by Jennifer Bresnick in HealthITAnalytics, include:

Capture of data

Cleansing of data

Storage of data

Security of data

Stewardship of data

Querying of data

Reporting of data

Visualization of data

Updating of datasets

Sharing data

It’s a big list of challenges and opportunities, but “In order to develop a big data exchange ecosystem that connects all members of the care continuum with trustworthy, timely, and meaningful information, providers will need to overcome every challenge on this list,” according to Bresnick.

What are some first steps that we can take? We need to gain the support and buy-in of our organizational leaders. HIM professionals should be strongly advocating within their organizations for a data governance strategy. Get the C-suite involved and make sure that everyone on the corporate ladder understands the importance. As Bresnick writes in another HealthITAnalytics article: “ignoring the role of data governance in the big data environment may be penny wise, pound foolish. Without robust, accurate, timely, clean, and complete data, healthcare organizations will not be able to move beyond the basics of record keeping and develop the analytics competencies that will become vital survival skills in the emerging world of value-based care.”

In a 2013 report from Kaiser Permanente, the University of Pennsylvania, and several public health institutes researchers strongly recommended the creation of “a set of guiding data governance principles that fit the mission, vision, and values of the particular provider,” according to Bresnick. It was further recommended to start with specific policies and procedures about data collection, paying particular attention to:

How people work together

Management of cross-functional conflicts

Decision-making and rights

Stewardship

Management of change

Resolution of issues

Making and enforcing rules

Management of cost and complexity

Creating value

Next, communicate to everyone in the organization, being sure to explain, give details, answer questions, and get buy-in for improvement activities that are planned. After the data governance leadership team has established a strong data governance vision and has gotten everyone on board, start with prioritizing projects that need to be improved on the data level. Take the time to train staff within the organization who are charged with creating, using, and sharing data. This could include areas such as clinical documentation improvement or patient registration.

The benefits for the healthcare organization will be seen on the financial side as well as quality side. And the goal, of course, would be improved patient outcomes. This project is not a one-and-done endeavor. Developing and sustaining the program is an ongoing process. To be sure, continued monitoring needs to exist, as well as continued improvements and reassessments. The organization and the data governance leadership team will need to continue training end-users, identifying roles as it relates to data governance activities, providing reminders about data integrity, and maintaining sound data entry practices. Audits should also be conducted within the organization to maintain high data quality.

As Bresnick writes, “These activities will ensure that healthcare providers are prepared to utilize their growing big data resources for generating actionable insights, and that they are being mindful of patient safety and care quality as they optimize their assets for the future of value-based care.” We need to be sure our information at the data level is accurate, reliable, and timely as we use it to make important business and clinical decisions. Data governance best practices are imperative for a successful information governance program and keeping up with the current in the Big Data era.

Researchers at the University of California, San Francisco, used previously untapped data buried in EHRs to pinpoint the source of a particularly nagging hospital-acquired infection.

The culprit? A CT scanner in the emergency department.

The UCSF researchers used time and location stamps in the system’s EHR to track the movements of more than 86,000 hospitalized patients over a three-year period. The results, published in JAMA Internal Medicine, showed patients who passed through the emergency department’s CT scanner within 24 hours after a patient with Clostridium difficile (C. diff), were twice as likely to become infected. Nearly 4% of patients who were exposed in the scanner became infected within two months.

Although previous studies tracking C. diff transmission have focused on a single hospital floor or even a hospital bed recently vacated by an infected patient, the UCSF study tracked nearly 435,000 patient movements throughout the entire hospital, which helped them build a comprehensive map of potential hotspots.

“If we just look at transmission in their room, we’re missing potential opportunities for disease transmission,” Russ Cucina, M.D., senior author on the study and chief health information officer at UCSF, said in a release. The researchers plan to continue exploring EHR data to track patient movements.

Time stamps in EHRs have shown to be increasingly valuable to researchers. A recent study out of Oregon Health and Science University found that time-stamp data can be helpful in evaluating physician workflows.

Providers have also leaned on EHRs to prevent infections like sepsis, although some experts have voiced concern that relying on electronic screenings could actually increase resistant superbugs by leading to increased use of broad-spectrum antibiotics.